population hiv viral load in swaziland: assessing art...
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Abstract # 96CROI, March 5, 2013 1
Jessica Justman1, Tanya M. Ellman2, Deborah Donnell3, Yen T. Duong4, Jason Reed4, George Bicego5, Peter
Ehrenkranz5, Joy Chang4, Lei Wang3, Naomi Bock4 and Rejoice Nkambule6
for the SHIMS Study Team1Columbia University, ICAP, Mailman School of Public Health, New York, United States, 2Columbia University Medical Center,
Medicine, New York, United States, 3Fred Hutchinson Cancer Research Center, Seattle, United States, 4Centers for Disease Control and Prevention, Atlanta, United States, 5Centers for Disease Control and Prevention, Mbabane, Swaziland, 6Ministry of Health -
Swaziland, Mbabane, Swaziland
Population HIV Viral Load in Swaziland:Assessing ART Program Effectiveness and
Transmission Potential
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The Kingdom of Swaziland
Population: 1.2 million
Highest HIV prevalence and incidence in the world: 26% in 2006 (DHS) and 2.7% (UNAIDS 2009)
HIV prevention campaign launched 2011—expanded male circumcision and ART—to curb epidemic
HIV incidence measurements needed to demonstrate impact
Adapted from WorldVision
Swaziland HIV Incidence Measurement SurveySHIMS
Cohorts: 18‐49 year old men and women
HIV Prevention and Treatment Campaign
Cohort 1 Cohort 2
Prevalence: 31%Incidence: 2.4%*
Follow-up Incidence
HIV Testing & HIV‐RNA* Nkambule, R et al. CROI 2012; Reed, J. et al., IAS 2012
Current Analysis:
To describe the distribution of HIV viral load in the Swaziland population
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Swaziland HIV Incidence Measurement Survey
CommunityViral Load
Population Viral Load
DiagnosedViral Load
TreatmentViral Load
Methods: Study Procedures
Survey of eligible household membersQuestionnaire & HIV testing/counseling
HIV-negative survey participants
Offer enrollment in incidence cohort
Select nationally-representative sample of households
Methods: Study Procedures
Survey of eligible household membersQuestionnaire & HIV testing/counseling
HIV-negative survey participants
HIV-positive survey participants
Offer enrollment in incidence cohort
HIV RNA measurements
Select/visit nationally-representative sample of households
Refer to HIV care & treatment
HIV RNA testing:• Blood samples collected from participants
and transported to National Reference Laboratory in Swaziland within 24 hours for processing into plasma aliquots
• All seropositive samples analyzed using automated platform:
Cobas AmpliPrep/Taqman HIV-1 test, v2.0• Limit of detection: 20 - 10,000,000
copies/ml
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SHIMS: Laboratory Methods
Viral load data are presented for the following:
Total: total population-based cohort
Unaware: unaware of HIV+ status prior to SHIMS
Aware: aware of HIV+ status
Not on ART: reported no current ART use
On ART: reported current use of ART
High viral load: >50,000 c/ml
Low viral load: <1,000 c/ml11
Definitions
SHIMS sample weighted to adjust for sampling methods and differences in non response and to achieve population representativeness
Statistical methods for multistage surveys used throughout
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Statistical Methods
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Results
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SHIMS PVL Cohort Participation
Participated 18,179* (74%)
HIV+5,802* (32%)
HIV-Neg12,370* (68%)
Refused 2,493* (10%)
No contact 3,812* (15%)
Total # potentially eligible household members: 24,484* (Dec ‘10- June ‘11)
*unweighted
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SHIMS PVL Cohort Participation
Viral load done 5828 (99%)
Aware of HIV+ diagnosis3,672 (63%)
No VL sample 13 (<1%)
Total HIV + participants 5,841†
Reports ART1763 (48%)
Unaware of HIV+ diagnosis2,156 (37%)
Reports No ART1909 (52%)†weighted
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HIV+ adults in Swaziland, age 18-49y
Sex
Men 34%
Women 66%
Marital status
Married/Partnered 55%
Single 45%
Age (years)
18-29 40%
30-39 39%
40-49 21%
Rural residence 70%
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Mean Population VL and Components
20,000
40,000
60,000
80,000
100,000
120,000
140,000
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TotalUnawareAware
Total and components
Mea
n HI
V-RN
A c
opie
s/m
l
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Mean Population VL and Components
20,000
40,000
60,000
80,000
100,000
120,000
140,000
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TotalUnawareAware On ARTNo ART
Total and components Aware and components
Mea
n HI
V-RN
A c
opie
s/m
l
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SHIMS: Mean and Median VL (c/ml)
Mean MedianTotal
n = 5,82894,644 14,471
Unawaren = 2,156
129,307 52,081
Awaren = 3,672
74,319 1,134
-Current ARTn = 1,763
22,979 0
-No ARTn = 1,909
129,260 39,755
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SHIMS: DISTRIBUTION OF VL
0%
20%
40%
60%
80%
100%
VL>50,000 c/ml
VL 1,000-49,999c/mlVL <1,000 c/ml
VL<20 c/ml
85%VL categories
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Distribution of VL by Sex and Age
VL <1,000 (%) VL >50,000 (%)Sex
Men 32% 44%Women 36% 30%
Age (years)18-29 22% 40%
30-39 41% 33%
40-49 49% 29%
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Multivariable Model: High VL >50,000 c/ml
High Viral Load (VL>50,000)Variable Level aOR* (95% CI) p-valueKnowledge of HIV+
Unaware of HIV+ status
14.6 (12., 17.77) <0.0001
Aware, No ART 13.2 (10.8, 16.07) <0.0001
Aware, Current ART 1.0
SexWomen 1.0
Men 1.96 (1.73, 2.22) <0.0001
Age (y)18-29 1.07 (0.91, 1.26) 0.4330
30-39 1.01 (0.86, 1.19) 0.9064
40-49 1.0*adjusted for regionand marital status
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Swaziland Cascade
0
20
40
60
80
100
HIV+ Aware on ART VL<1000 VL<20
63%
25%of all
Of all with HIV infection in Swaziland, 35%, regardless of ART use, have viral suppression <1000 c/ml
~35%
Per
cent
age
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Swaziland Cascade
0
20
40
60
80
100
HIV+ Aware on ART VL<1000
63%
Of all with HIV infection in Swaziland, 28% have ART-related viral suppression <1000 c/ml
~28%
Per
cent
age
• First national estimate of population viral load, performed among a household-based, nationally representative HIV+ group
• Unique opportunity to compare aggregate VL measures across different groups
• VL distribution of unaware and untreated similar
• Men twice as likely to have high VL• Independent of being less likely to be
diagnosed 25
Summary
• Evidence of an effective ART program • 85% of those who report current ART use
have VL<1000
• Yet transmission potential is high, with 65% of HIV+ adults, regardless of ART use, not virally suppressed
• Time to move to precise terminology in describing estimates of HIV viral load in order to “know your epidemic”
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Conclusions
Thanks to the women and men in SHIMS
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AcknowledgementsProtocol Team*Rejoice Nkambule*George Bicego*Naomi BockMuhle DlaminiDeborah DonnellDennis EllenbergerTedd EllerbrockWafaa El-SadrJonathan Grund*Jessica JustmanAmy MedleyJan MooreEmmanuel Njeuhmeli*Jason ReedNelisiweSikhosana
ICAP at Columbia UniversityElizabeth BaroneMontina BefusMary DiehlBriana FerrignoMark FussellAllison GoldbergLeslie HornJacqueline MaxwellJoan MonserrateNeena PhilipPeter TwymanLeah Westra Allison Zerbe
Nat’l Ref LaboratoryHosea SukatiSindi DlaminiAll Laboratory Scientists
CDC AtlantaAnindya DeJoy ChangJosh DeVosYen DuongDennis EllenbergerAl GarciaCarole MooreJohn NkengasongMichele OwenBharat ParekhHetal PatelConnie SextonChunfu Yang
CDC SwazilandPeter EhrenkranzAhmed LibanKhosi Makhanya
SCHARPClaire ChapduLynda EmelIraj MohebalianLei WangCherry MaoKeala LiCasey Herron
Epicentre/MaromiHealth Research Cherie CawoodMark ColvinDavid KhanyileNomsa NzamaPhindile RadebeAll Regional ManagersAll field teams
ICAP in SwazilandAlfred AdamsKerry BruceGcinekile DlaminiNdumisi DlaminiSindisiwe DlaminiHenry GinindzaSibuse GinindzaAlison KolerYvonne MavengereKhudzie MlamboPhakamileNdlangamandlaIngrid PetersonNicola PierceBhangazi Zwane
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Acknowledgements
Swaziland Ministry of Healthand
Central Statistical Office